Towards robust identification and tracking of nevi in sparse photographic time series

Jakob Vogel, Alexandru Duliu, Yuji Oyamada, Jose Gardiazabal, Tobias Lasser, Mahzad Ziai, Rüdiger Hein, Nassir Navab

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    In dermatology, photographic imagery is acquired in large volumes in order to monitor the progress of diseases, especially melanocytic skin cancers. For this purpose, overview (macro) images are taken of the region of interest and used as a reference map to re-localize highly magni ed images of individual lesions. The latter are then used for diagnosis. These pictures are acquired at irregular intervals under only partially constrained circumstances, where patient positions as well as camera positions are not reliable. In the presence of a large number of nevi, correct identi cation of the same nevus in a series of such images is thus a time consuming task with ample chances for error. This paper introduces a method for largely automatic and simultaneous identi cation of nevi in di erent images, thus allowing the tracking of a single nevus over time, as well as pattern evaluation. The method uses a rotation-invariant feature descriptor that uses the local neighborhood of a nevus to describe it. The texture, size and shape of the nevus are not used to describe it, as these can change over time, especially in the case of a malignancy. We then use the Random Walks framework to compute the correspondences based on the probabilities derived from comparing the feature vectors. Evaluation is performed on synthetic and patient data at the university clinic.

    Original languageEnglish
    Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
    PublisherSPIE
    Volume9035
    ISBN (Print)9780819498281
    DOIs
    Publication statusPublished - 2014
    EventMedical Imaging 2014: Computer-Aided Diagnosis - San Diego, CA
    Duration: 2014 Feb 182014 Feb 20

    Other

    OtherMedical Imaging 2014: Computer-Aided Diagnosis
    CitySan Diego, CA
    Period14/2/1814/2/20

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    Keywords

    • Biomedical Imaging
    • Dermatology
    • Feature Descriptor
    • Random Walks
    • Robust Matching

    ASJC Scopus subject areas

    • Atomic and Molecular Physics, and Optics
    • Electronic, Optical and Magnetic Materials
    • Biomaterials
    • Radiology Nuclear Medicine and imaging

    Cite this

    Vogel, J., Duliu, A., Oyamada, Y., Gardiazabal, J., Lasser, T., Ziai, M., Hein, R., & Navab, N. (2014). Towards robust identification and tracking of nevi in sparse photographic time series. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 9035). [90353D] SPIE. https://doi.org/10.1117/12.2043788